Name: BrentChoi
Type: User
Company: Foxconn Industrial Internet
Bio: Master's degree in computer science at NTUST. Interested in AI including Computer Vision & NLP Analysis, Developing Android, and Firmware.
Location: Taiwan
Blog: https://www.linkedin.com/in/hyunmin-choi
BrentChoi's Projects
資通訊科技趨勢與Python教學
A simple recommender system based on Collaborative Filtering for implicit feedback dataset
This repo will house all our course material and code snippets from the Introduction to Machine Learning Class
Learn OpenCV : C++ and Python Examples
Install and run GNU/Linux on Android
A collection of machine learning examples and tutorials.
Your phone is your PC.
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
Unity Machine Learning Agents Toolkit
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.
Implemented Content-based filtering, Collaborative filtering and K-Means Clustering on MovieLens Dataset(https://www.kaggle.com/rounakbanik/the-movies-dataset/data)
4 different recommendation engines for the MovieLens dataset.
Multi Text Classificaiton
An Open-source Neural Hierarchical Multi-label Text Classification Toolkit
Parallel Feature Pyramid Network for Object Detection in tensorflow
파이썬을 활용한 데이터 분석과 이미지 처리 - 강의 자료 및 소스코드 Repository입니다.
An introduction to recommendation systems in Python
Repository for the Recommender Systems Challenge 2020/2021 @ PoliMi
recommender system tutorial with Python
This is the repository of our article published in RecSys 2019 "Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches" and of several follow-up studies.
A simplified implemention of Faster R-CNN that replicate performance from origin paper
Android terminal app for devices with a serial / UART interface connected with a USB-to-serial-converter
This repo will present a system that predictesbinary results of judgment, deploying state-of-art, further building a DL hybrid model that is a combination of DLs that have different hypnosis on the analyzing data level. This is also realated to the my thesis topic.In this repo, I will use other judgment related other dataset and employ more advanced method and hypothesis to get not only better result but also more unserstandble and visuable results.
The new Windows Terminal and the original Windows console host, all in the same place!
🚘 A Ruby gem and unofficial documentation of Tesla's JSON API for the Model S, 3, X, and Y.